Psychometric qualities of the White Bear Suppression Inventory in a Dutch sample of children and adolescents

The White Bear Suppression Inventory [WBSI; Wegner and Zanakos (1994)] was developed to assess the tendency to suppress unwanted thoughts. Most psychometric studies of the WBSI have included healthy students and adults with obsessive-compulsive disorder. There has been increasing interest in thought suppression in children and adolescents, especially after a traumatic event, but little is known about the psychometric properties of the WBSI for children. The aim of this research was to examine the psychometric qualities of the WBSI in a Dutch sample of children and adolescents. Two studies were conducted. First, the WBSI’s factor structure, internal consistency and test-retest stability were examined in a sample of 203 primary school children (9-13 years). Second, the factor structure and content validity were assessed in 89 children and adolescents (8-18 years) who attended the emergency room after a road traffic accident. Results demonstrated that the WBSI items contribute to a single factor measuring the suppression of unwanted thoughts and that the reliability is satisfactory. Associations between the WBSI and PTSD-symptoms demonstrated sufficient content validity. The findings suggest that the WBSI can appropriately be used in child and adolescent samples.     

Understanding memory impairment with memory models and hierarchical Bayesian analysis

The study of human episodic memory is a topic that interests cognitive and mathematical psychologists as well as clinicians interested in the diagnosis and assessment of Alzheimer’s disease and related disorders (ADRD). In this paper, we use simple cognitive models for the recognition and recall tasks typically applied in clinical assessments of ADRD to study memory performance in ADRD patients. Our models make use of hierarchical Bayesian methods as a way to model individual differences in patient performance and to facilitate the modeling of performance changes that occur during multiple recall tasks. We show how the models are able to account for different aspects of patient performance, and also discuss some of the predictive capabilities of the model. We conclude with a discussion on the scope to improve on our results by discussing the link between memory theory in psychology and clinical practice.     

No evidence for a General Factor of Personality in the HEXACO Personality Inventory

There have been an increasing number of articles that have speculated on the existence of a General Factor of Personality (GFP) similar to ‘g’ in intelligence research. In this study, I provide evidence that this general factor may be an artifact of the personality instrument used. Specifically, in two samples I show that depending on the type of analysis used there is either no evidence for a GFP in the HEXACO Personality Inventory or the GFP is found to be uncorrelated to GFPs based on Big Five or FFM instruments.     

The three latent classes of adolescent delinquency and the risk factors for membership in each class

This study used latent class analysis to examine subpopulation membership based on self-reports of delinquent behaviors obtained from Australian youth. Three discrete identifiable classes were derived based on 51 indicators of physical violence, property damage, minor infractions, drug use, and social delinquency. One class of youth engaged in primarily rule breaking and norm violations including underage alcohol use, typical of this age period. A second class was more actively delinquent emphasizing drug use, trespassing, and various forms of disobedience. A third class of highly delinquent youth differed from their counterparts by endorsing drug use, thievery that involved stealing money, goods, and cars, property damage, gambling, precocious sexual experiences, involvement with pornographic materials, and fighting. Multinomial logistic regression predicting class membership indicated highly delinquent youth were more likely to be older males, use venting coping strategies, and be fun or novelty seeking compared with rule breakers. Findings are discussed in terms of refining current taxonomic arguments regarding the structure of delinquency and implications for prevention of early-stage antisocial behavior.     

Sex differences in latent cognitive abilities ages 5 to 17: Evidence from the Differential Ability Scales—Second Edition

Sex differences in the latent general and broad cognitive abilities underlying the Differential Ability Scales, Second Edition were investigated for children and youth ages 5 through 17. Multi-group mean and covariance structural equation modeling was used to investigate sex differences in latent cognitive abilities as well as changes in these differences across age. Most broad abilities showed mean differences across the sexes, and all such differences varied across ages. Girls showed an advantage on the processing speed (Gs) first-order residual factor. Girls also showed advantages at some ages on free-recall memory, a narrow ability of long term retrieval (Glr). Boys showed a developmentally-related advantage on a visual-spatial ability (Gv) first-order residual factor, depending on age. Younger girls showed an advantage on short-term memory (Gsm). No statistically significant sex differences were shown on the latent comprehension-knowledge (Gc) factor, or on a second-order, latent g factor. Boys showed larger variances for several broad abilities, some substantial, but those differences were not statistically significant.     

潜变量交互效应标准化估计：方法比较与选用策略

标准化估计对模型的解释和效应大小的比较有重要作用。虽然潜变量交互效应的恰当标准化估计公式已经面世超过10年, 国内外都在使用和引用, 但至今未见到关于不同估计方法得到的恰当标准化估计的系统比较。通过模拟实验, 比较了乘积指标法、潜调节结构方程(LMS)、无先验信息和有先验信息的贝叶斯法的潜变量交互效应标准化估计在不同条件下的表现。结果发现, 在正态条件下, LMS和有信息贝叶斯法表现较好; 而在非正态条件下, 乘积指标法比较稳健, 但需要较大的样本(不小于500), 小样本且外生潜变量之间相关很低时可使用无信息贝叶斯法。     

Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data

Considering the high crash rates involving pedestrians on urban roads, it is highly relevant to understanding pedestrian crossing behavior. This paper is the first to combine stated preference (SP) and revealed preference (RP) data to evaluate the impact that individual attributes, trip characteristics, built environment, strategies to prevent unauthorized crossing, and traffic flows have on pedestrians crossing decisions in an urban context. SP and RP surveys were designed and collected in Barranquilla (Colombia) near pedestrian bridges or signalized intersections where direct crossings and a high concentration of pedestrian fatalities related to traffic accidents exist. A logit model was estimated using the data enrichment paradigm. Results show that pedestrians weigh risks and costs when choosing how to cross the road. The trajectories observed in the RP component suggest that people prefer direct crossings; nevertheless, pedestrian bridges and signalized intersections can be attractive alternatives if their location matches the origin or destination of the crossing, and no detour is needed to use them. Waiting time; safety; the fine imposed for jaywalking; personal security, and previous decisions are also variables that influence pedestrian behavior when crossing urban roads. These results can be helpful to urban planners and decision-makers interested in proposing appropriate pedestrian infrastructure. The data pooling technique and the inclusion of a cost-related variable (i.e., fine) allowed computing the willingness to pay and marginal substitution rates for attributes of the built environment and other characteristics associated with the crossing decision. Also, the inclusion of several crossing alternatives and situations allowed assessing pedestrian crossing preferences under different scenarios.     

Cognitive technology to capture deep computational concepts with combinators

Computational activity is now recognized as a natural science, and computational and information processes have been discovered in the deep structures of many areas. Computations in the natural world were present long before the invention of computers, but a remarkable shift in understanding its fundamental nature occurs, in fact, before our eyes. The present moment, in fact, is a transition from the concept of computer science as an artificial science to the understanding that information processes are abundant in nature. Computing is recognized as a natural science that studies natural and artificial information processes.In everyday computing, operations are performed on the individual generators, with little attention paid to their internal structure. However, many common operations consist of more primitive constructions connected by a combination mode. The interaction of information processes and corresponding structures is carried out in an environment of “applicative interaction”, their applications to each other, and the study of the properties of this environment allows us to understand the nature of the computations.In the present work, the main attention is paid to elucidating the technological features of computations with individual generators, or objects. Their interaction is considered in an applicative environment, which allows us to elucidate the internal structure of ordinary operations, the knowledge of which allows us to understand their properties. The choice of initial constant generators, considered as generic ones and expressed by combinators, is discussed. These initial generators are used as the main “building blocks” that occur within the larger blocks of the applicative environment in interaction with each other. As a result of the interaction, constructions arise that give representative sets of ordinary operators and embedded computing systems.     

国内调节效应的方法学研究

在心理学和其他社科研究领域, 大量实证文章建立调节效应模型, 以分析自变量对因变量的影响是如何随着调节变量的变化而改变。过去10多年, 调节效应分析成了方法学研究的一个热点。从显变量的调节效应、潜变量的调节效应、多层数据的调节效应、基于两层回归模型的单层调节分析、纵向数据的调节效应、调节和中介的整合模型六个主题系统地总结了国内调节效应分析的方法学研究的发展历程。最后对调节效应的未来研究方向做了讨论和拓展。